> Markdown version of [/jobs/ext/2237862-full-stack-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2237862-full-stack-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack AI Engineer - **Company:** Compunnel Inc. - **Location:** Richardson, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Continuous Integration, Python (Programming Language), Web Applications, Enterprise Data Management, Google Cloud, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Kubernetes, Graphql, Front End Software Development, Virtual Agents, GPT, Automation Anywhere, Docker, Web Api, Microservices - **Published:** August 26, 2026 - **Apply:** https://www.dice.com/job-detail/c6260436-0b17-41c6-aa2b-a7f1d0f2fe19 ## About the Role Job Summary We are seeking a highly skilled, hands-on Full Stack AI Engineer to design, build, and deploy next-generation Agentic AI solutions and automated workflows. The role bridges LLM technologies and production-grade software using frameworks such as LangGraph and CrewAI to build autonomous AI systems. The position will also involve integrating AI agents with cloud platforms, APIs, and enterprise data platforms such as Snowflake. Key Responsibilities Design and deploy multi-agent systems, autonomous AI agents, and intelligent workflow automation using LLMs such as Claude, GPT, and Gemini. Build scalable backend services, REST/GraphQL APIs, microservices, and modern web application interfaces supporting AI features. Implement AI orchestration, Retrieval-Augmented Generation (RAG) pipelines, vector database embeddings, and custom tool/function calling. Integrate AI solutions with cloud platforms, Snowflake, enterprise data platforms, and external APIs. Optimize model performance and manage prompt engineering pipelines. Deploy secure and reliable GenAI features in production environments. Develop and maintain production-grade AI workflows and enterprise integrations. Required Qualifications Advanced production-level Python development skills. Hands-on experience working with frontier Generative AI models including OpenAI GPT, Anthropic Claude, and Google Gemini. Hands-on experience with Agentic AI and orchestration frameworks such as LangGraph, CrewAI, AutoGen, LangChain, LlamaIndex, or Semantic Kernel. Solid experience building RAG architectures using vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or Chroma. Experience with native tool/function calling. Proficiency in building REST/GraphQL APIs, microservices, and modern web application frontends. Experience deploying AI workflows into enterprise cloud environments. Experience interfacing with databases and enterprise platforms such as Snowflake. Preferred Qualifications Experience with AI coding assistants and agentic CLI tools such as Claude Code. Strong understanding of CI/CD and containerization using Docker and Kubernetes. Experience with AWS, Azure, or Google Cloud Platform cloud infrastructure. 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